Computer Aided Surgery最新文献

Three hundred and eighty computer-assisted total knee arthroplasty cases were reviewed for accuracy of mechanical alignment. The 331 patients in the first set, designated Group A, showed a consistent valgus error of 1° from neutral alignment. It was hypothesized that a manual 1° varus correction during femur resection would yield a significantly greater level of accuracy in the second set of 49 patients, designated Group B. A mechanical alignment of ±3° was achieved in 91% of the uncalibrated Group A patients, which was significantly lower (p = 0.035) than the rate of 98% achieved in the calibrated Group B. Further statistical analysis of the data showed the time expenditure was not significantly changed once a new target value was recalibrated. By quantifying mean errors of measures at an early timeframe, enhanced accuracy in CAS can be achieved.

The evolution of surgical robotics is following the progress of developments in Minimally Invasive Surgery (MIS), which is moving towards Single-Incision Laparoscopic Surgery (SILS) procedures. The complexity of these techniques has favored the introduction of robotic surgical systems. New bimanual robots, which are completely inserted into the patient's body, have been proposed in order to enhance the surgical gesture in SILS procedures. However, the limited laparoscopic view and the focus on the end-effectors, together with the use of complex robotic devices inside the patient's abdomen, may lead to unexpected collisions, e.g., between the surrounding anatomical organs not involved in the intervention and the surgical robot. This paper describes a computer guidance system, based on patient-specific data, designed to provide intraoperative navigation and assistance in SILS robotic interventions. The navigator has been tested in simulations of some of the surgical tasks involved in a cholecystectomy, using a synthetic anthropomorphic mannequin. The results demonstrate the usability and efficacy of the navigation system, underlining the importance of avoiding unwanted collisions between the robot arms and critical organs. The proposed computer guidance software is able to integrate any bimanual surgical robot design.

High Intensity Focused Ultrasound (HIFU) has been successfully applied in tumor therapy. For a successful HIFU therapy, it is crucial to localize the tumor region accurately. In this paper, we present a semi-automatic non-rigid registration method for implementing image guided surgery navigation and localization by matching pre-operative CT/MR images and intra-operative ultrasound images. The global motion of the target is modeled by an affine transformation, while the local deformation of the target is described by Free-Form Deformation (FFD) based on B-splines. The results of our experiments on simulated and real data show that the non-rigid registration method based on HPV interpolation (partial volume based on the Hanning windowed sinc function) is effective at restraining local extrema and improves the accuracy of registration results. A preliminary clinical validation of the use of the non-rigid registration method in image guided localization of a HIFU system is also reported.

The aim of this paper is to analyze the variations in registration accuracy for computer-assisted surgical navigation using three different modes of registration, in order to explore the behavior of random error, and to highlight the precision of neuronavigation as a concept distinct from accuracy. The operational accuracy of three different registration modes (bone fiducials, scalp adhesive fiducials and an auto-registration mask) was evaluated in a total of 20 fresh cadaveric heads. The precision of the neuronavigation system was then assessed by evaluating the variation in the accuracy measurements associated with each registration mode. The coefficient of variation was employed to quantify the degree of variation in the attained accuracy using the following formula: Coefficient of variation = standard deviation/mean * 100. For external targets, the precision of the neuronavigation system was greatest with mask registration (43.75 and 51.41 for anterior and posterior external targets, respectively) and lowest with bone registration (65.30 and 67.17 for anterior and posterior external targets, respectively). For internal targets, the precision of the neuronavigation system was greatest with bone registration (47.69 and 42.6 for anterior and posterior internal targets, respectively) and lowest with mask registration (62.9 and 58.67 for anterior and posterior internal targets, respectively). The precision (reproducibility) of the neuronavigation system is another important quantity besides accuracy that characterizes the performance of the system. Understanding both of these quantities for a given registration mode enhances the use of a neuronavigation system in neurosurgery.

A computational model is proposed to demonstrate the feasibility of characterizing the motion of lung tumors caused by respiratory diaphragm forces using a tissue biomechanics approach. Compensating for such motion is very important for developing effective systems of minimally invasive tumor ablative procedures, e.g., Low Dose Rate (LDR) lung brachytherapy. To minimize the effects of respiratory motion, the target lung is almost completely deflated before starting such procedures. However, a significant amount of motion persists in the target lung due to the diaphragm contact forces required for the other lung's respiration. In this study, a model pipeline was developed which inputs a pre-operative 4D-CT image sequence of the lung to output the predicted 3D motion trajectory of the tumor over the respiratory cycle. A finite element method was used in this pipeline to model the lung tissue deformation in order to predict the tumor motion. Experiments were conducted on an ex vivo porcine lung to demonstrate the performance and assess the accuracy of the proposed pipeline. The resultant tumor motion trajectory obtained from the biomechanical model of the lung was compared to the experimental trajectory obtained from CT imaging. Results were promising, suggesting that tissue mechanics-based modeling can be employed for effective characterization of lung tumor respiratory motion to improve accuracy in lung tumor ablative procedures.

Surgical techniques are becoming more complex and require substantial training to master. The development of automated, objective methods to analyze and evaluate surgical skill is necessary to provide trainees with reliable and accurate feedback during their training programs. We present a system to capture, visualize, and analyze the movements of a laparoscopic surgeon for the purposes of skill evaluation. The system records the upper body movement of the surgeon, the position, and orientation of the instruments, and the force and torque applied to the instruments. An empirical study was conducted using the system to record the performances of a number of surgeons with a wide range of skill. The study validated the usefulness of the system, and demonstrated the accuracy of the measurements.

Introduction: The trend of surgical robotics is to follow the evolution of laparoscopy, which is now moving towards single-incision laparoscopic surgery. The main drawback of this approach is the limited maneuverability of the surgical tools. Promising solutions to improve the surgeon's dexterity are based on bimanual robots. However, since both robot arms are completely inserted into the patient's body, issues related to possible unwanted collisions with structures adjacent to the target organ may arise.

Materials and methods: This paper presents a simulator based on patient-specific data for the positioning and workspace evaluation of bimanual surgical robots in the pre-operative planning of single-incision laparoscopic surgery.

Results: The simulator, designed for the pre-operative planning of robotic laparoscopic interventions, was tested by five expert surgeons who evaluated its main functionalities and provided an overall rating for the system.

Discussion: The proposed system demonstrated good performance and usability, and was designed to integrate both present and future bimanual surgical robots.

Introduction: During the application of a hinged external elbow fixator, exact placement of the central pin remains difficult. Proper placement often necessitates multiple drilling attempts and fluoroscopic localization, which can be time consuming. We hypothesized that use of computerized navigation would enable a more precise placement of the central axis pin and would reduce the total number of drilling attempts.

Materials and methods: Twelve elbow models incorporating soft tissue coverage were used in this study. First, the optimal placement trajectory (OPJ) of the axis pin was defined in the anterior-posterior (AP) and lateral planes of the elbow. Six elbows were used with the navigation system and the axis pin was inserted in combination with a conventional fluoroscopy system under constant two-dimensional guidance from the virtual images. The pins for the remaining six elbow specimens were implanted conventionally under fluoroscopic guidance. The distances and angular deviations from the OPJ position were measured, and the results for the conventional placement and computer navigation groups were compared. To determine the definitive axis pin placement, a CT scan of each elbow with 1-mm slice thickness was used and the results were measured based on the defined optimal pin placement. AP plane angulations and lateral plane distances were calculated in relation to the optimal insertion trajectory for each specimen. Finally, we counted the overall number of drilling attempts needed to find the optimal position for the axis pin.

Results: For the AP angulations, of the six elbows implanted using the conventional technique, half (n=3) had deviations of ≥20° from the optimal axis. In contrast, in the navigated group, all cases (n=6) were within 20° of the optimal axis in the AP plane. The mean AP angulation deviation in the conventional group was 20.5°, compared to 15° in the navigation group (p=0.077). For the lateral distances, the mean distance from the drilling point to the point of optimal placement was 3.83 mm in the conventional group, versus 1.83 mm in the navigation group (p=0.042). For all navigated cases, only one drilling attempt was necessary to achieve the desired position of the axial pin.

Conclusion: Compared with the conventional method of axis pin placement for an elbow fixator, two-dimensional navigation allows a reduction in the number of drilling attempts required. Furthermore, the accuracy in terms of AP angulation and lateral distance from a defined optimal placement is better when compared to that obtained with the conventional technique.

Objective: The widespread use of image guided surgery in the frontolateral skull base region has been limited by the need for a reliable and non-invasive registration procedure that provides sub-millimetric accuracy. We developed and validated preclinically a non-invasive, easy-to-use registration device based on a dental splint with a laterally mounted fiducial carrier.

Methods: Repeated accuracy measurements were performed on six titanium target fiducials which were screwed into the lateral skull base region of a cadaver head and could be unequivocally identified both on the CT image and in reality. The system accuracy was evaluated by determining the deviation of the real target position from the position indicated in the CT scan. The accuracy of the dental splint-based registration was compared to that of two standard registration procedures: contour-based laser surface registration and fixed marker registration.

Results: The mean accuracy of 0.55±0.28 mm obtained when using the maxillary splint device was similar to that obtained with the "gold standard" registration using bone-implanted markers (0.33±0.26 mm), while being clearly superior to that obtained with contour-based laser surface registration (1.91±0.74 mm).

Conclusions: Registration using the non-invasively fixed maxillary fiducial platform can provide sub-millimetric accuracy in the lateral skull base region. In vivo validation may prove dental splint-based registration to be an accurate and non-invasive alternative option for image guided surgery of the lateral skull base, and may facilitate the application of navigation systems in this delicate region.

Femoral intramedullary guides have been shown to be insufficiently accurate in creating a distal femoral resection perpendicular to the mechanical axis in total knee arthroplasty (TKA), as they make assumptions regarding the difference between the patient's femoral mechanical and anatomical angles. The aim of this cadaveric study was to validate the accuracy of a portable accelerometer-based navigation device for alignment of the distal femoral cutting block in TKA. Twenty-nine trials were performed on five cadaveric specimens (hip-to-ankle), in which the distal femoral cutting block was placed using the KneeAlign 2™ navigation device. For each specimen, a preoperative "target" was assigned for varus/valgus and flexion/extension alignment of the cutting block. The actual alignment of each cutting block was then measured using the ORTHOsoft Computer Assisted Surgery (CAS) system. The mean absolute difference between the preoperative target and the alignment of the cutting block was 0.83 ± 0.60° for varus/valgus, and 0.83 ± 0.83° for flexion/extension. The KneeAlign 2™ navigation device can set and align the distal femoral resection guide with the same accuracy as a large-console CAS system, thus demonstrating that portable accelerometer-based navigation can be used reliably in total knee arthroplasty.